Data gathered from various telecommunication companies (e.g.cable, phone, internet service providers) and utility companies (electric, fuel, etc.) were merged into
One data warehouse.Suppose the goal of data mining using this data warehouse was to
Predict whether a household's telecommunication needs will increase, decrease or stay
The same over the next year.What technique might be most appropriate for achieving
This goal?
A)Neural network.
B)Supervised problem.
C)Tree model.
D)Nodal network.
E)None of the above.

Question

Quizplus · Accepted Answer

The most appropriate technique for predicting whether a household's telecommunication needs will increase, decrease, or stay the same over the next year would be a tree model. This is because a tree model can handle multiple variables and identify the most significant predictors for the outcome of interest. Additionally, a tree model is easy to interpret and can help identify subgroups within the data that may have different patterns of telecommunications needs. Other techniques like neural networks or nodal networks may be suitable for other types of data mining goals but may not be the best choice for this particular objective. A supervised problem is a general category that includes tree models, neural networks, and other techniques. Therefore, it is not the most accurate answer to this particular question.

Data Gathered from Various Telecommunication Companies (E